Overview

Dataset statistics

Number of variables22
Number of observations19077
Missing cells0
Missing cells (%)0.0%
Duplicate rows16
Duplicate rows (%)0.1%
Total size in memory3.1 MiB
Average record size in memory169.0 B

Variable types

Categorical3
Boolean1
Numeric18

Alerts

Dataset has 16 (0.1%) duplicate rowsDuplicates
dataplus is highly overall correlated with questionnaireHigh correlation
dualpane is highly overall correlated with oucontent and 1 other fieldsHigh correlation
folder is highly overall correlated with pageHigh correlation
forumng is highly overall correlated with homepage and 3 other fieldsHigh correlation
homepage is highly overall correlated with forumng and 5 other fieldsHigh correlation
oucontent is highly overall correlated with dualpane and 6 other fieldsHigh correlation
ouwiki is highly overall correlated with homepage and 3 other fieldsHigh correlation
page is highly overall correlated with folder and 4 other fieldsHigh correlation
questionnaire is highly overall correlated with dataplus and 3 other fieldsHigh correlation
quiz is highly overall correlated with oucontent and 1 other fieldsHigh correlation
resource is highly overall correlated with forumng and 3 other fieldsHigh correlation
subpage is highly overall correlated with forumng and 6 other fieldsHigh correlation
url is highly overall correlated with forumng and 4 other fieldsHigh correlation
repeatactivity is highly imbalanced (99.9%)Imbalance
sharedsubpage is highly imbalanced (97.8%)Imbalance
glossary is highly skewed (γ1 = 26.7980793)Skewed
resource is highly skewed (γ1 = 27.94158756)Skewed
dataplus has 16897 (88.6%) zerosZeros
dualpane has 16016 (84.0%) zerosZeros
externalquiz has 15459 (81.0%) zerosZeros
folder has 17309 (90.7%) zerosZeros
forumng has 1303 (6.8%) zerosZeros
glossary has 14467 (75.8%) zerosZeros
htmlactivity has 17850 (93.6%) zerosZeros
oucollaborate has 10954 (57.4%) zerosZeros
oucontent has 1036 (5.4%) zerosZeros
ouelluminate has 17047 (89.4%) zerosZeros
ouwiki has 10554 (55.3%) zerosZeros
page has 12578 (65.9%) zerosZeros
questionnaire has 15593 (81.7%) zerosZeros
quiz has 4833 (25.3%) zerosZeros
resource has 510 (2.7%) zerosZeros
subpage has 294 (1.5%) zerosZeros
url has 2836 (14.9%) zerosZeros

Reproduction

Analysis started2023-03-13 20:44:00.481437
Analysis finished2023-03-13 20:45:23.584118
Duration1 minute and 23.1 seconds
Software versionydata-profiling vv4.1.0
Download configurationconfig.json

Variables

Distinct22
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size149.2 KiB
FFF 2013_October
1414 
BBB 2013_October
1371 
BBB 2014_October
1339 
FFF 2014_October
 
1247
DDD 2013_October
 
1147
Other values (17)
12559 

Length

Max length17
Median length16
Mean length16.380458
Min length16

Characters and Unicode

Total characters312490
Distinct characters24
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGGG 2013_October
2nd rowEEE 2013_October
3rd rowGGG 2013_October
4th rowFFF 2014_October
5th rowBBB 2014_October

Common Values

ValueCountFrequency (%)
FFF 2013_October 1414
 
7.4%
BBB 2013_October 1371
 
7.2%
BBB 2014_October 1339
 
7.0%
FFF 2014_October 1247
 
6.5%
DDD 2013_October 1147
 
6.0%
CCC 2014_October 1110
 
5.8%
FFF 2013_February 1076
 
5.6%
BBB 2013_February 1062
 
5.6%
DDD 2014_October 1041
 
5.5%
BBB 2014_February 928
 
4.9%
Other values (12) 7342
38.5%

Length

2023-03-13T16:45:23.697695image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2014_october 6206
16.3%
2013_october 5613
14.7%
bbb 4700
12.3%
fff 4658
12.2%
2014_february 4317
11.3%
ddd 3603
9.4%
2013_february 2941
7.7%
ccc 1945
 
5.1%
eee 1827
 
4.8%
ggg 1766
 
4.6%

Most occurring characters

ValueCountFrequency (%)
r 26335
 
8.4%
F 21232
 
6.8%
_ 19077
 
6.1%
19077
 
6.1%
b 19077
 
6.1%
e 19077
 
6.1%
1 19077
 
6.1%
0 19077
 
6.1%
2 19077
 
6.1%
B 14100
 
4.5%
Other values (14) 117284
37.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 121720
39.0%
Uppercase Letter 76308
24.4%
Decimal Number 76308
24.4%
Connector Punctuation 19077
 
6.1%
Space Separator 19077
 
6.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 26335
21.6%
b 19077
15.7%
e 19077
15.7%
c 11819
9.7%
t 11819
9.7%
o 11819
9.7%
u 7258
 
6.0%
a 7258
 
6.0%
y 7258
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
F 21232
27.8%
B 14100
18.5%
O 11819
15.5%
D 10809
14.2%
C 5835
 
7.6%
E 5481
 
7.2%
G 5298
 
6.9%
A 1734
 
2.3%
Decimal Number
ValueCountFrequency (%)
1 19077
25.0%
0 19077
25.0%
2 19077
25.0%
4 10523
13.8%
3 8554
11.2%
Connector Punctuation
ValueCountFrequency (%)
_ 19077
100.0%
Space Separator
ValueCountFrequency (%)
19077
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 198028
63.4%
Common 114462
36.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 26335
13.3%
F 21232
10.7%
b 19077
9.6%
e 19077
9.6%
B 14100
 
7.1%
c 11819
 
6.0%
t 11819
 
6.0%
o 11819
 
6.0%
O 11819
 
6.0%
D 10809
 
5.5%
Other values (7) 40122
20.3%
Common
ValueCountFrequency (%)
_ 19077
16.7%
19077
16.7%
1 19077
16.7%
0 19077
16.7%
2 19077
16.7%
4 10523
9.2%
3 8554
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312490
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 26335
 
8.4%
F 21232
 
6.8%
_ 19077
 
6.1%
19077
 
6.1%
b 19077
 
6.1%
e 19077
 
6.1%
1 19077
 
6.1%
0 19077
 
6.1%
2 19077
 
6.1%
B 14100
 
4.5%
Other values (14) 117284
37.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size18.8 KiB
True
12358 
False
6719 
ValueCountFrequency (%)
True 12358
64.8%
False 6719
35.2%
2023-03-13T16:45:23.820036image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

dataplus
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct85
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8158515
Minimum0
Maximum143
Zeros16897
Zeros (%)88.6%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:23.921577image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile14
Maximum143
Range143
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.2333209
Coefficient of variation (CV)3.9834319
Kurtosis46.243716
Mean1.8158515
Median Absolute Deviation (MAD)0
Skewness5.8645031
Sum34641
Variance52.320931
MonotonicityNot monotonic
2023-03-13T16:45:24.097551image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 16897
88.6%
1 225
 
1.2%
3 121
 
0.6%
8 101
 
0.5%
4 99
 
0.5%
6 89
 
0.5%
5 88
 
0.5%
7 88
 
0.5%
2 84
 
0.4%
10 80
 
0.4%
Other values (75) 1205
 
6.3%
ValueCountFrequency (%)
0 16897
88.6%
1 225
 
1.2%
2 84
 
0.4%
3 121
 
0.6%
4 99
 
0.5%
5 88
 
0.5%
6 89
 
0.5%
7 88
 
0.5%
8 101
 
0.5%
9 74
 
0.4%
ValueCountFrequency (%)
143 1
< 0.1%
101 1
< 0.1%
100 2
< 0.1%
99 1
< 0.1%
97 1
< 0.1%
93 1
< 0.1%
91 1
< 0.1%
86 1
< 0.1%
80 1
< 0.1%
78 2
< 0.1%

dualpane
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.89877863
Minimum0
Maximum69
Zeros16016
Zeros (%)84.0%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:24.264849image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum69
Range69
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.1190432
Coefficient of variation (CV)3.470313
Kurtosis58.265455
Mean0.89877863
Median Absolute Deviation (MAD)0
Skewness6.0393819
Sum17146
Variance9.7284306
MonotonicityNot monotonic
2023-03-13T16:45:24.427197image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 16016
84.0%
1 673
 
3.5%
2 482
 
2.5%
3 358
 
1.9%
4 268
 
1.4%
5 205
 
1.1%
6 176
 
0.9%
7 134
 
0.7%
8 130
 
0.7%
9 104
 
0.5%
Other values (30) 531
 
2.8%
ValueCountFrequency (%)
0 16016
84.0%
1 673
 
3.5%
2 482
 
2.5%
3 358
 
1.9%
4 268
 
1.4%
5 205
 
1.1%
6 176
 
0.9%
7 134
 
0.7%
8 130
 
0.7%
9 104
 
0.5%
ValueCountFrequency (%)
69 2
< 0.1%
49 1
< 0.1%
46 1
< 0.1%
45 1
< 0.1%
43 1
< 0.1%
40 1
< 0.1%
39 2
< 0.1%
36 2
< 0.1%
34 1
< 0.1%
33 1
< 0.1%

externalquiz
Real number (ℝ)

Distinct100
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9275043
Minimum0
Maximum340
Zeros15459
Zeros (%)81.0%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:24.556548image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile19
Maximum340
Range340
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10.097041
Coefficient of variation (CV)3.4490269
Kurtosis149.53788
Mean2.9275043
Median Absolute Deviation (MAD)0
Skewness8.2111926
Sum55848
Variance101.95024
MonotonicityNot monotonic
2023-03-13T16:45:24.728761image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 15459
81.0%
1 320
 
1.7%
4 240
 
1.3%
2 240
 
1.3%
3 236
 
1.2%
5 174
 
0.9%
6 163
 
0.9%
7 145
 
0.8%
9 141
 
0.7%
8 138
 
0.7%
Other values (90) 1821
 
9.5%
ValueCountFrequency (%)
0 15459
81.0%
1 320
 
1.7%
2 240
 
1.3%
3 236
 
1.2%
4 240
 
1.3%
5 174
 
0.9%
6 163
 
0.9%
7 145
 
0.8%
8 138
 
0.7%
9 141
 
0.7%
ValueCountFrequency (%)
340 1
< 0.1%
316 1
< 0.1%
169 2
< 0.1%
164 2
< 0.1%
129 1
< 0.1%
119 1
< 0.1%
114 1
< 0.1%
113 1
< 0.1%
111 1
< 0.1%
109 1
< 0.1%

folder
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.26613199
Minimum0
Maximum13
Zeros17309
Zeros (%)90.7%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:25.355766image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum13
Range13
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.98056838
Coefficient of variation (CV)3.684519
Kurtosis28.742322
Mean0.26613199
Median Absolute Deviation (MAD)0
Skewness4.7595361
Sum5077
Variance0.96151436
MonotonicityNot monotonic
2023-03-13T16:45:25.505113image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 17309
90.7%
2 509
 
2.7%
3 435
 
2.3%
1 350
 
1.8%
4 236
 
1.2%
5 119
 
0.6%
6 53
 
0.3%
7 32
 
0.2%
8 15
 
0.1%
9 5
 
< 0.1%
Other values (4) 14
 
0.1%
ValueCountFrequency (%)
0 17309
90.7%
1 350
 
1.8%
2 509
 
2.7%
3 435
 
2.3%
4 236
 
1.2%
5 119
 
0.6%
6 53
 
0.3%
7 32
 
0.2%
8 15
 
0.1%
9 5
 
< 0.1%
ValueCountFrequency (%)
13 3
 
< 0.1%
12 2
 
< 0.1%
11 5
 
< 0.1%
10 4
 
< 0.1%
9 5
 
< 0.1%
8 15
 
0.1%
7 32
 
0.2%
6 53
 
0.3%
5 119
0.6%
4 236
1.2%

forumng
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1828
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean319.97903
Minimum0
Maximum13154
Zeros1303
Zeros (%)6.8%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:25.666403image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q134
median132
Q3352
95-th percentile1168
Maximum13154
Range13154
Interquartile range (IQR)318

Descriptive statistics

Standard deviation636.72645
Coefficient of variation (CV)1.9899005
Kurtosis70.550556
Mean319.97903
Median Absolute Deviation (MAD)119
Skewness6.7084677
Sum6104240
Variance405420.57
MonotonicityNot monotonic
2023-03-13T16:45:25.804078image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1303
 
6.8%
1 189
 
1.0%
3 185
 
1.0%
2 183
 
1.0%
4 167
 
0.9%
5 150
 
0.8%
6 149
 
0.8%
7 132
 
0.7%
8 132
 
0.7%
9 129
 
0.7%
Other values (1818) 16358
85.7%
ValueCountFrequency (%)
0 1303
6.8%
1 189
 
1.0%
2 183
 
1.0%
3 185
 
1.0%
4 167
 
0.9%
5 150
 
0.8%
6 149
 
0.8%
7 132
 
0.7%
8 132
 
0.7%
9 129
 
0.7%
ValueCountFrequency (%)
13154 1
< 0.1%
11465 1
< 0.1%
11344 1
< 0.1%
10483 1
< 0.1%
9919 1
< 0.1%
9666 1
< 0.1%
9560 1
< 0.1%
9320 1
< 0.1%
9292 1
< 0.1%
9279 1
< 0.1%

glossary
Real number (ℝ)

SKEWED  ZEROS 

Distinct175
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5053205
Minimum0
Maximum1364
Zeros14467
Zeros (%)75.8%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:25.922086image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile11
Maximum1364
Range1364
Interquartile range (IQR)0

Descriptive statistics

Standard deviation31.645296
Coefficient of variation (CV)9.0277895
Kurtosis900.7435
Mean3.5053205
Median Absolute Deviation (MAD)0
Skewness26.798079
Sum66871
Variance1001.4248
MonotonicityNot monotonic
2023-03-13T16:45:26.087649image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 14467
75.8%
1 1308
 
6.9%
2 673
 
3.5%
3 414
 
2.2%
4 301
 
1.6%
5 250
 
1.3%
6 185
 
1.0%
7 158
 
0.8%
8 117
 
0.6%
12 103
 
0.5%
Other values (165) 1101
 
5.8%
ValueCountFrequency (%)
0 14467
75.8%
1 1308
 
6.9%
2 673
 
3.5%
3 414
 
2.2%
4 301
 
1.6%
5 250
 
1.3%
6 185
 
1.0%
7 158
 
0.8%
8 117
 
0.6%
9 96
 
0.5%
ValueCountFrequency (%)
1364 1
< 0.1%
1316 1
< 0.1%
1213 1
< 0.1%
1169 1
< 0.1%
1157 1
< 0.1%
1127 1
< 0.1%
1003 1
< 0.1%
916 1
< 0.1%
874 1
< 0.1%
699 1
< 0.1%

homepage
Real number (ℝ)

Distinct1412
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean294.47114
Minimum0
Maximum8543
Zeros15
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:26.325212image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile17
Q188
median194
Q3379
95-th percentile882
Maximum8543
Range8543
Interquartile range (IQR)291

Descriptive statistics

Standard deviation362.40525
Coefficient of variation (CV)1.2306987
Kurtosis69.138336
Mean294.47114
Median Absolute Deviation (MAD)128
Skewness5.6249773
Sum5617626
Variance131337.56
MonotonicityNot monotonic
2023-03-13T16:45:26.490274image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 74
 
0.4%
2 72
 
0.4%
1 72
 
0.4%
59 72
 
0.4%
4 68
 
0.4%
100 67
 
0.4%
3 67
 
0.4%
29 67
 
0.4%
44 65
 
0.3%
49 65
 
0.3%
Other values (1402) 18388
96.4%
ValueCountFrequency (%)
0 15
 
0.1%
1 72
0.4%
2 72
0.4%
3 67
0.4%
4 68
0.4%
5 58
0.3%
6 74
0.4%
7 46
0.2%
8 53
0.3%
9 48
0.3%
ValueCountFrequency (%)
8543 2
< 0.1%
7277 1
< 0.1%
6430 2
< 0.1%
5548 1
< 0.1%
5114 1
< 0.1%
4752 1
< 0.1%
4664 1
< 0.1%
4622 1
< 0.1%
4596 1
< 0.1%
4507 1
< 0.1%

htmlactivity
Real number (ℝ)

Distinct26
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.30701892
Minimum0
Maximum33
Zeros17850
Zeros (%)93.6%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:26.641173image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum33
Range33
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.4402693
Coefficient of variation (CV)4.6911418
Kurtosis68.332114
Mean0.30701892
Median Absolute Deviation (MAD)0
Skewness6.8434656
Sum5857
Variance2.0743757
MonotonicityNot monotonic
2023-03-13T16:45:26.766089image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0 17850
93.6%
4 189
 
1.0%
3 185
 
1.0%
2 184
 
1.0%
5 155
 
0.8%
1 122
 
0.6%
6 122
 
0.6%
7 94
 
0.5%
8 53
 
0.3%
9 40
 
0.2%
Other values (16) 83
 
0.4%
ValueCountFrequency (%)
0 17850
93.6%
1 122
 
0.6%
2 184
 
1.0%
3 185
 
1.0%
4 189
 
1.0%
5 155
 
0.8%
6 122
 
0.6%
7 94
 
0.5%
8 53
 
0.3%
9 40
 
0.2%
ValueCountFrequency (%)
33 1
 
< 0.1%
27 1
 
< 0.1%
25 1
 
< 0.1%
24 1
 
< 0.1%
23 2
< 0.1%
22 1
 
< 0.1%
20 1
 
< 0.1%
18 1
 
< 0.1%
17 2
< 0.1%
16 3
< 0.1%

oucollaborate
Real number (ℝ)

Distinct136
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.7810977
Minimum0
Maximum316
Zeros10954
Zeros (%)57.4%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:26.910254image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile25
Maximum316
Range316
Interquartile range (IQR)4

Descriptive statistics

Standard deviation12.927816
Coefficient of variation (CV)2.7039431
Kurtosis79.923818
Mean4.7810977
Median Absolute Deviation (MAD)0
Skewness6.9021149
Sum91209
Variance167.12843
MonotonicityNot monotonic
2023-03-13T16:45:27.088132image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10954
57.4%
1 1505
 
7.9%
2 1066
 
5.6%
3 654
 
3.4%
4 585
 
3.1%
5 450
 
2.4%
6 328
 
1.7%
7 310
 
1.6%
8 269
 
1.4%
9 250
 
1.3%
Other values (126) 2706
 
14.2%
ValueCountFrequency (%)
0 10954
57.4%
1 1505
 
7.9%
2 1066
 
5.6%
3 654
 
3.4%
4 585
 
3.1%
5 450
 
2.4%
6 328
 
1.7%
7 310
 
1.6%
8 269
 
1.4%
9 250
 
1.3%
ValueCountFrequency (%)
316 1
 
< 0.1%
248 2
< 0.1%
227 1
 
< 0.1%
224 1
 
< 0.1%
217 1
 
< 0.1%
193 1
 
< 0.1%
186 2
< 0.1%
172 1
 
< 0.1%
171 1
 
< 0.1%
162 3
< 0.1%

oucontent
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct2468
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean485.14462
Minimum0
Maximum9928
Zeros1036
Zeros (%)5.4%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:27.277910image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q136
median196
Q3649
95-th percentile1906.4
Maximum9928
Range9928
Interquartile range (IQR)613

Descriptive statistics

Standard deviation724.59829
Coefficient of variation (CV)1.4935717
Kurtosis17.182356
Mean485.14462
Median Absolute Deviation (MAD)187
Skewness3.1767541
Sum9255104
Variance525042.68
MonotonicityNot monotonic
2023-03-13T16:45:27.447133image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1036
 
5.4%
1 602
 
3.2%
2 303
 
1.6%
3 157
 
0.8%
4 152
 
0.8%
5 122
 
0.6%
7 117
 
0.6%
6 113
 
0.6%
10 110
 
0.6%
12 101
 
0.5%
Other values (2458) 16264
85.3%
ValueCountFrequency (%)
0 1036
5.4%
1 602
3.2%
2 303
 
1.6%
3 157
 
0.8%
4 152
 
0.8%
5 122
 
0.6%
6 113
 
0.6%
7 117
 
0.6%
8 82
 
0.4%
9 97
 
0.5%
ValueCountFrequency (%)
9928 2
< 0.1%
8672 1
< 0.1%
8328 1
< 0.1%
8314 1
< 0.1%
7814 2
< 0.1%
7780 2
< 0.1%
7264 2
< 0.1%
7063 1
< 0.1%
6860 1
< 0.1%
6700 2
< 0.1%

ouelluminate
Real number (ℝ)

Distinct120
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7620171
Minimum0
Maximum317
Zeros17047
Zeros (%)89.4%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:27.598507image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile9
Maximum317
Range317
Interquartile range (IQR)0

Descriptive statistics

Standard deviation9.1477285
Coefficient of variation (CV)5.191623
Kurtosis156.14313
Mean1.7620171
Median Absolute Deviation (MAD)0
Skewness9.8142798
Sum33614
Variance83.680937
MonotonicityNot monotonic
2023-03-13T16:45:27.746759image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 17047
89.4%
1 305
 
1.6%
2 202
 
1.1%
3 157
 
0.8%
4 96
 
0.5%
5 87
 
0.5%
6 76
 
0.4%
7 67
 
0.4%
9 64
 
0.3%
8 60
 
0.3%
Other values (110) 916
 
4.8%
ValueCountFrequency (%)
0 17047
89.4%
1 305
 
1.6%
2 202
 
1.1%
3 157
 
0.8%
4 96
 
0.5%
5 87
 
0.5%
6 76
 
0.4%
7 67
 
0.4%
8 60
 
0.3%
9 64
 
0.3%
ValueCountFrequency (%)
317 1
< 0.1%
176 1
< 0.1%
171 1
< 0.1%
166 2
< 0.1%
147 1
< 0.1%
142 1
< 0.1%
134 1
< 0.1%
131 1
< 0.1%
130 1
< 0.1%
129 1
< 0.1%

ouwiki
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct560
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.021754
Minimum0
Maximum2117
Zeros10554
Zeros (%)55.3%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:27.941761image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q334
95-th percentile212
Maximum2117
Range2117
Interquartile range (IQR)34

Descriptive statistics

Standard deviation96.031117
Coefficient of variation (CV)2.399473
Kurtosis43.781192
Mean40.021754
Median Absolute Deviation (MAD)0
Skewness5.0538968
Sum763495
Variance9221.9755
MonotonicityNot monotonic
2023-03-13T16:45:28.099352image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 10554
55.3%
1 377
 
2.0%
2 252
 
1.3%
3 200
 
1.0%
4 167
 
0.9%
6 155
 
0.8%
5 152
 
0.8%
9 126
 
0.7%
11 125
 
0.7%
8 119
 
0.6%
Other values (550) 6850
35.9%
ValueCountFrequency (%)
0 10554
55.3%
1 377
 
2.0%
2 252
 
1.3%
3 200
 
1.0%
4 167
 
0.9%
5 152
 
0.8%
6 155
 
0.8%
7 115
 
0.6%
8 119
 
0.6%
9 126
 
0.7%
ValueCountFrequency (%)
2117 1
< 0.1%
1637 2
< 0.1%
1217 1
< 0.1%
1191 1
< 0.1%
1111 1
< 0.1%
1102 1
< 0.1%
1076 1
< 0.1%
1045 1
< 0.1%
1035 1
< 0.1%
1028 1
< 0.1%

page
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct64
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5776065
Minimum0
Maximum334
Zeros12578
Zeros (%)65.9%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:28.276876image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile14
Maximum334
Range334
Interquartile range (IQR)2

Descriptive statistics

Standard deviation6.2540587
Coefficient of variation (CV)2.4263046
Kurtosis427.51384
Mean2.5776065
Median Absolute Deviation (MAD)0
Skewness10.758588
Sum49173
Variance39.11325
MonotonicityNot monotonic
2023-03-13T16:45:28.571235image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12578
65.9%
1 1094
 
5.7%
2 783
 
4.1%
3 645
 
3.4%
4 524
 
2.7%
5 452
 
2.4%
6 380
 
2.0%
7 317
 
1.7%
9 293
 
1.5%
8 286
 
1.5%
Other values (54) 1725
 
9.0%
ValueCountFrequency (%)
0 12578
65.9%
1 1094
 
5.7%
2 783
 
4.1%
3 645
 
3.4%
4 524
 
2.7%
5 452
 
2.4%
6 380
 
2.0%
7 317
 
1.7%
8 286
 
1.5%
9 293
 
1.5%
ValueCountFrequency (%)
334 1
 
< 0.1%
74 1
 
< 0.1%
69 1
 
< 0.1%
68 1
 
< 0.1%
65 1
 
< 0.1%
64 3
< 0.1%
62 1
 
< 0.1%
61 1
 
< 0.1%
59 1
 
< 0.1%
58 2
< 0.1%

questionnaire
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct62
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5040101
Minimum0
Maximum65
Zeros15593
Zeros (%)81.7%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:28.897006image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile17
Maximum65
Range65
Interquartile range (IQR)0

Descriptive statistics

Standard deviation7.3060257
Coefficient of variation (CV)2.9177302
Kurtosis16.007268
Mean2.5040101
Median Absolute Deviation (MAD)0
Skewness3.8177876
Sum47769
Variance53.378011
MonotonicityNot monotonic
2023-03-13T16:45:29.085133image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 15593
81.7%
3 485
 
2.5%
9 261
 
1.4%
6 210
 
1.1%
4 191
 
1.0%
10 176
 
0.9%
12 172
 
0.9%
1 148
 
0.8%
7 137
 
0.7%
11 126
 
0.7%
Other values (52) 1578
 
8.3%
ValueCountFrequency (%)
0 15593
81.7%
1 148
 
0.8%
2 52
 
0.3%
3 485
 
2.5%
4 191
 
1.0%
5 81
 
0.4%
6 210
 
1.1%
7 137
 
0.7%
8 93
 
0.5%
9 261
 
1.4%
ValueCountFrequency (%)
65 1
 
< 0.1%
63 1
 
< 0.1%
62 1
 
< 0.1%
59 1
 
< 0.1%
58 2
< 0.1%
57 1
 
< 0.1%
55 2
< 0.1%
54 3
< 0.1%
53 3
< 0.1%
52 2
< 0.1%

quiz
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1767
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean317.31032
Minimum0
Maximum13032
Zeros4833
Zeros (%)25.3%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:29.330486image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median95
Q3485
95-th percentile1218
Maximum13032
Range13032
Interquartile range (IQR)485

Descriptive statistics

Standard deviation551.26626
Coefficient of variation (CV)1.7373096
Kurtosis50.989509
Mean317.31032
Median Absolute Deviation (MAD)95
Skewness4.9426626
Sum6053329
Variance303894.49
MonotonicityNot monotonic
2023-03-13T16:45:29.571114image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4833
 
25.3%
1 295
 
1.5%
2 136
 
0.7%
74 103
 
0.5%
80 96
 
0.5%
75 95
 
0.5%
78 95
 
0.5%
70 94
 
0.5%
73 92
 
0.5%
79 91
 
0.5%
Other values (1757) 13147
68.9%
ValueCountFrequency (%)
0 4833
25.3%
1 295
 
1.5%
2 136
 
0.7%
3 84
 
0.4%
4 69
 
0.4%
5 35
 
0.2%
6 34
 
0.2%
7 28
 
0.1%
8 20
 
0.1%
9 22
 
0.1%
ValueCountFrequency (%)
13032 1
< 0.1%
10829 1
< 0.1%
8877 1
< 0.1%
8323 2
< 0.1%
7693 1
< 0.1%
7164 1
< 0.1%
6883 2
< 0.1%
6569 1
< 0.1%
6523 2
< 0.1%
6129 1
< 0.1%

repeatactivity
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size149.2 KiB
0
19075 
2
 
1
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters19077
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 19075
> 99.9%
2 1
 
< 0.1%
3 1
 
< 0.1%

Length

2023-03-13T16:45:29.808548image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-13T16:45:30.000966image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 19075
> 99.9%
2 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 19075
> 99.9%
2 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19077
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19075
> 99.9%
2 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 19077
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19075
> 99.9%
2 1
 
< 0.1%
3 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19077
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19075
> 99.9%
2 1
 
< 0.1%
3 1
 
< 0.1%

resource
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct398
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.663784
Minimum0
Maximum5147
Zeros510
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:30.259940image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q114
median31
Q360
95-th percentile150
Maximum5147
Range5147
Interquartile range (IQR)46

Descriptive statistics

Standard deviation96.579696
Coefficient of variation (CV)1.9446705
Kurtosis1255.9493
Mean49.663784
Median Absolute Deviation (MAD)21
Skewness27.941588
Sum947436
Variance9327.6377
MonotonicityNot monotonic
2023-03-13T16:45:30.473107image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 510
 
2.7%
9 355
 
1.9%
5 339
 
1.8%
6 338
 
1.8%
3 336
 
1.8%
14 336
 
1.8%
12 335
 
1.8%
8 331
 
1.7%
4 327
 
1.7%
15 321
 
1.7%
Other values (388) 15549
81.5%
ValueCountFrequency (%)
0 510
2.7%
1 316
1.7%
2 297
1.6%
3 336
1.8%
4 327
1.7%
5 339
1.8%
6 338
1.8%
7 317
1.7%
8 331
1.7%
9 355
1.9%
ValueCountFrequency (%)
5147 1
< 0.1%
4635 2
< 0.1%
4562 1
< 0.1%
2808 1
< 0.1%
2281 1
< 0.1%
1850 1
< 0.1%
1825 1
< 0.1%
1472 1
< 0.1%
874 1
< 0.1%
827 1
< 0.1%

sharedsubpage
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size149.2 KiB
0
18981 
1
 
77
2
 
13
3
 
5
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters19077
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 18981
99.5%
1 77
 
0.4%
2 13
 
0.1%
3 5
 
< 0.1%
4 1
 
< 0.1%

Length

2023-03-13T16:45:30.785931image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-03-13T16:45:31.146808image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
0 18981
99.5%
1 77
 
0.4%
2 13
 
0.1%
3 5
 
< 0.1%
4 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 18981
99.5%
1 77
 
0.4%
2 13
 
0.1%
3 5
 
< 0.1%
4 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19077
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18981
99.5%
1 77
 
0.4%
2 13
 
0.1%
3 5
 
< 0.1%
4 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 19077
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18981
99.5%
1 77
 
0.4%
2 13
 
0.1%
3 5
 
< 0.1%
4 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19077
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18981
99.5%
1 77
 
0.4%
2 13
 
0.1%
3 5
 
< 0.1%
4 1
 
< 0.1%

subpage
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct918
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean147.86932
Minimum0
Maximum4346
Zeros294
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:31.529249image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q125
median76
Q3212
95-th percentile500
Maximum4346
Range4346
Interquartile range (IQR)187

Descriptive statistics

Standard deviation187.65634
Coefficient of variation (CV)1.2690688
Kurtosis26.111454
Mean147.86932
Median Absolute Deviation (MAD)63
Skewness3.2353926
Sum2820903
Variance35214.901
MonotonicityNot monotonic
2023-03-13T16:45:32.286519image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 294
 
1.5%
11 226
 
1.2%
1 212
 
1.1%
18 200
 
1.0%
6 194
 
1.0%
4 193
 
1.0%
5 193
 
1.0%
15 192
 
1.0%
9 190
 
1.0%
2 190
 
1.0%
Other values (908) 16993
89.1%
ValueCountFrequency (%)
0 294
1.5%
1 212
1.1%
2 190
1.0%
3 176
0.9%
4 193
1.0%
5 193
1.0%
6 194
1.0%
7 171
0.9%
8 189
1.0%
9 190
1.0%
ValueCountFrequency (%)
4346 1
< 0.1%
2688 1
< 0.1%
2453 2
< 0.1%
2303 2
< 0.1%
1862 1
< 0.1%
1846 1
< 0.1%
1619 1
< 0.1%
1614 1
< 0.1%
1576 1
< 0.1%
1570 1
< 0.1%

url
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct267
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.287886
Minimum0
Maximum2134
Zeros2836
Zeros (%)14.9%
Negative0
Negative (%)0.0%
Memory size149.2 KiB
2023-03-13T16:45:33.055739image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median12
Q332
95-th percentile84
Maximum2134
Range2134
Interquartile range (IQR)29

Descriptive statistics

Standard deviation40.288575
Coefficient of variation (CV)1.658793
Kurtosis447.42164
Mean24.287886
Median Absolute Deviation (MAD)11
Skewness12.245321
Sum463340
Variance1623.1693
MonotonicityNot monotonic
2023-03-13T16:45:33.462887image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2836
 
14.9%
1 934
 
4.9%
2 769
 
4.0%
3 754
 
4.0%
4 625
 
3.3%
5 569
 
3.0%
6 524
 
2.7%
8 509
 
2.7%
7 500
 
2.6%
9 404
 
2.1%
Other values (257) 10653
55.8%
ValueCountFrequency (%)
0 2836
14.9%
1 934
 
4.9%
2 769
 
4.0%
3 754
 
4.0%
4 625
 
3.3%
5 569
 
3.0%
6 524
 
2.7%
7 500
 
2.6%
8 509
 
2.7%
9 404
 
2.1%
ValueCountFrequency (%)
2134 1
< 0.1%
830 1
< 0.1%
820 1
< 0.1%
729 1
< 0.1%
646 2
< 0.1%
635 1
< 0.1%
633 1
< 0.1%
612 2
< 0.1%
592 1
< 0.1%
573 1
< 0.1%

Interactions

2023-03-13T16:45:19.116128image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:02.374534image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:05.120286image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:07.852421image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:10.472114image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:21.129561image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:24.973999image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:28.625297image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:32.926970image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:35.258638image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:38.050970image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:42.116500image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:45.959407image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:50.276204image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:54.197891image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:01.285236image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:09.192984image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:14.002916image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:19.357263image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:02.566374image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:05.288806image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:07.989043image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:10.633283image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:21.464599image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:25.223257image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:29.640920image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:33.041375image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:35.394027image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:38.288733image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:42.308748image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:46.204645image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:50.440847image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:54.458858image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:01.876990image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:09.475372image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:14.257451image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:19.571267image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:02.726589image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:05.540092image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:08.183082image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:10.759624image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:21.715344image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:25.455914image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:29.941642image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:33.165321image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:35.547457image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:38.477477image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:42.522804image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:46.513344image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:50.552275image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:54.947350image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:02.641998image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:09.711345image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:14.460217image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:19.828187image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:02.912085image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:05.647978image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:08.335265image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:10.913152image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:22.021335image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:25.635713image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:30.171331image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:33.297181image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:35.709565image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:38.648687image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:42.773008image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:46.859199image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:50.671075image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:55.480824image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:03.179238image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:09.922778image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:14.709163image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:20.032302image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:03.061087image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:05.764089image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:08.484343image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:11.066491image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:22.213225image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:25.783935image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:30.413623image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:33.427098image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:35.829038image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:38.801870image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:42.973673image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:47.169238image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:50.813308image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:55.821606image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:03.527777image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:10.177600image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:14.943183image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:20.262871image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:03.179090image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:05.909742image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:08.654321image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:11.236911image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:22.405747image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:25.963882image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:30.627968image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:33.557278image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:35.950385image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:39.028796image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:43.174955image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:47.439379image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:51.047925image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:56.093633image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:04.012069image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:10.390722image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:15.165147image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:20.499101image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:03.305436image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:06.056133image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:08.823658image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:17.817405image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:22.590926image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:26.435827image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:30.905253image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:33.689622image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:36.117200image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:39.377913image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:43.370586image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:47.719171image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:51.283025image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:56.330981image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:04.368182image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:10.844832image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:15.464622image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:20.710927image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:03.482794image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:06.186333image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:08.941077image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:18.053459image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:22.774378image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:26.605061image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:31.150132image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:33.804881image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:36.264464image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:39.620761image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:43.566048image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:48.003123image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:51.478398image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:56.538645image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:05.091908image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:11.111392image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:15.715982image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:20.905752image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:03.652279image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:06.327075image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:09.113388image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:18.528471image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:22.929658image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:26.773444image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:31.427369image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:33.940341image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:36.378129image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:39.843079image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:43.763172image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:48.248150image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:51.676670image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:56.802791image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:05.474395image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:11.363968image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:15.983490image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:21.092145image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:03.778404image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:06.478095image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:09.242113image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:18.835326image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:23.112477image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:26.925657image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:31.644928image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:34.085394image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:36.517745image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:40.566433image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:43.958128image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:48.441009image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:51.859047image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:57.065713image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:05.840833image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:11.617367image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:16.276521image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
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2023-03-13T16:44:19.079237image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:23.322824image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:27.099395image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:31.836961image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:34.231392image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:36.652549image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:40.767100image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:44.113479image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:48.643104image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:52.021543image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:57.328348image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:06.171017image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:11.909137image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:16.592803image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:21.476062image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:04.064591image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:06.771240image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:09.493517image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:19.482555image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:23.477063image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:27.268989image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:32.012195image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:34.364949image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:36.806085image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:40.948524image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:44.249981image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:48.814120image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:52.201531image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:57.610881image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:06.509206image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:12.226923image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:16.876186image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:21.673978image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:04.222174image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:06.953309image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:09.635807image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:19.779493image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:23.637655image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:27.441580image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:32.137268image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:34.483330image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:36.911124image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:41.095301image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:44.398813image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:49.104158image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:52.426364image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:58.577076image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:06.858915image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:12.632253image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:17.145080image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:21.831831image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:04.348543image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:07.103060image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:09.765405image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:20.025764image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:23.804017image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:27.601855image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:32.275873image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:34.603381image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:37.059108image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:41.248800image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:44.687539image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:49.362318image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:52.623343image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:58.862703image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:07.236545image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:12.896668image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:17.712981image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:22.051091image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:04.475055image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:07.268133image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:09.930320image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:20.208596image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:23.981433image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:27.761005image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:32.394199image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:34.757823image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:37.265442image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:41.398759image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:44.896515image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:49.562665image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:52.832887image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:59.181127image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:07.591887image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:13.130734image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:18.090181image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:22.271540image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:04.618332image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:07.427332image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:10.066149image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:20.429740image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:24.182149image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:27.972122image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:32.550197image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:34.878053image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:37.442210image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:41.599419image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:45.120070image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:49.772207image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:53.235289image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:59.629423image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:07.937761image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:13.369197image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:18.395419image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:22.468984image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:04.790069image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:07.601482image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:10.202229image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:20.621920image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:24.360328image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:28.156053image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:32.698646image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:35.007905image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:37.598729image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:41.789908image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:45.421105image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:49.971377image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:53.703789image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:00.024947image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:08.391344image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:13.613308image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:18.633876image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:22.642122image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:04.940390image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:07.719722image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:10.332210image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:20.826435image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:24.635502image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:28.378057image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:32.811174image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:35.110340image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:37.795197image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:41.988071image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:45.693371image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:50.134344image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:44:53.945178image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:00.688183image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:08.873461image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:13.823472image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
2023-03-13T16:45:18.893931image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Correlations

2023-03-13T16:45:33.852109image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
dataplusdualpaneexternalquizfolderforumngglossaryhomepagehtmlactivityoucollaborateoucontentouelluminateouwikipagequestionnairequizresourcesubpageurlcourse_year_monthpass_courserepeatactivitysharedsubpage
dataplus1.0000.480-0.1680.3660.279-0.0600.3710.2600.0920.4840.1400.2290.4720.5930.3410.1540.4100.3230.1210.1390.0000.000
dualpane0.4801.000-0.1990.3130.266-0.1400.3570.0910.0860.5060.1760.4230.4590.5140.4470.1310.3270.3670.1500.0900.0000.000
externalquiz-0.168-0.1991.000-0.1500.1750.2010.185-0.1220.288-0.0820.1680.318-0.143-0.221-0.4300.3350.3340.2570.1530.0570.0000.000
folder0.3660.313-0.1501.0000.180-0.0800.245-0.0750.1580.354-0.0940.2010.5030.4210.4080.1190.3430.1750.2300.1400.0220.000
forumng0.2790.2660.1750.1801.0000.1910.7990.1020.3640.3980.2310.4360.3120.2660.3030.5080.6250.6550.0400.1130.0190.083
glossary-0.060-0.1400.201-0.0800.1911.0000.173-0.0740.120-0.0030.039-0.133-0.175-0.016-0.1290.2550.1050.0300.0320.0300.0000.000
homepage0.3710.3570.1850.2450.7990.1731.0000.1410.4310.6540.2110.5370.4190.3810.4780.6990.7840.7430.0460.1330.0640.019
htmlactivity0.2600.091-0.122-0.0750.102-0.0740.1411.0000.1360.252-0.0840.1360.2580.3110.2600.0460.2400.1000.2410.0530.0000.000
oucollaborate0.0920.0860.2880.1580.3640.1200.4310.1361.0000.349-0.2380.3270.1210.1800.1410.3840.4030.3400.1200.1030.0000.000
oucontent0.4840.506-0.0820.3540.398-0.0030.6540.2520.3491.0000.0890.5450.5340.5750.5610.3920.5700.4330.1610.2240.0000.000
ouelluminate0.1400.1760.168-0.0940.2310.0390.211-0.084-0.2380.0891.0000.2180.2900.1500.0460.1780.2790.2710.1480.0400.0000.000
ouwiki0.2290.4230.3180.2010.436-0.1330.5370.1360.3270.5450.2181.0000.4240.2650.2730.3460.5400.5990.1670.1200.0000.000
page0.4720.459-0.1430.5030.312-0.1750.4190.2580.1210.5340.2900.4241.0000.5700.5970.2720.5960.3690.0680.0240.0790.000
questionnaire0.5930.514-0.2210.4210.266-0.0160.3810.3110.1800.5750.1500.2650.5701.0000.4910.2030.4220.2290.1810.1720.0000.000
quiz0.3410.447-0.4300.4080.303-0.1290.4780.2600.1410.5610.0460.2730.5970.4911.0000.3080.4200.2840.0920.1010.0620.000
resource0.1540.1310.3350.1190.5080.2550.6990.0460.3840.3920.1780.3460.2720.2030.3081.0000.7260.5130.0140.0160.0000.000
subpage0.4100.3270.3340.3430.6250.1050.7840.2400.4030.5700.2790.5400.5960.4220.4200.7261.0000.6930.1040.1420.0540.000
url0.3230.3670.2570.1750.6550.0300.7430.1000.3400.4330.2710.5990.3690.2290.2840.5130.6931.0000.0480.0390.0000.000
course_year_month0.1210.1500.1530.2300.0400.0320.0460.2410.1200.1610.1480.1670.0680.1810.0920.0140.1040.0481.0000.1150.0000.078
pass_course0.1390.0900.0570.1400.1130.0300.1330.0530.1030.2240.0400.1200.0240.1720.1010.0160.1420.0390.1151.0000.0040.013
repeatactivity0.0000.0000.0000.0220.0190.0000.0640.0000.0000.0000.0000.0000.0790.0000.0620.0000.0540.0000.0000.0041.0000.000
sharedsubpage0.0000.0000.0000.0000.0830.0000.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0780.0130.0001.000

Missing values

2023-03-13T16:45:22.933089image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-03-13T16:45:23.354371image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

course_year_monthpass_coursedataplusdualpaneexternalquizfolderforumngglossaryhomepagehtmlactivityoucollaborateoucontentouelluminateouwikipagequestionnairequizrepeatactivityresourcesharedsubpagesubpageurl
0GGG 2013_OctoberTrue00000051005000006505080
1EEE 2013_OctoberTrue02005250706001788019300371077021560
2GGG 2013_OctoberTrue00004522750062800001580770150
3FFF 2014_OctoberTrue00004110470399640145191001020025437
4BBB 2014_OctoberTrue0000109423502647800001180840260
5EEE 2014_OctoberTrue00001223082000737046210146012012379
6CCC 2014_OctoberTrue00805990491039910110024804109444
7BBB 2013_FebruaryFalse00005201300000000011002
8EEE 2013_OctoberTrue030027502670058702590025701303523
9DDD 2014_FebruaryTrue00120383030202242033000043014928
course_year_monthpass_coursedataplusdualpaneexternalquizfolderforumngglossaryhomepagehtmlactivityoucollaborateoucontentouelluminateouwikipagequestionnairequizrepeatactivityresourcesharedsubpagesubpageurl
19067FFF 2013_FebruaryFalse0000004002000013300081
19068FFF 2013_OctoberTrue0301181021106535067030801201283
19069AAA 2013_OctoberTrue30009901560156900000060333
19070DDD 2014_FebruaryFalse000011322000165029000074031426
19071BBB 2014_FebruaryFalse000010600000001300040
19072EEE 2014_FebruaryTrue0000210151023940100002370801733
19073BBB 2013_FebruaryFalse00001804700100004703053
19074FFF 2014_FebruaryFalse000011021012500301010270
19075BBB 2014_FebruaryTrue0000212016100390000800291354
19076EEE 2014_OctoberFalse0000203100720000202003

Duplicate rows

Most frequently occurring

course_year_monthpass_coursedataplusdualpaneexternalquizfolderforumngglossaryhomepagehtmlactivityoucollaborateoucontentouelluminateouwikipagequestionnairequizrepeatactivityresourcesharedsubpagesubpageurl# duplicates
2BBB 2013_OctoberFalse000000100000000000005
15GGG 2014_FebruaryFalse000000100000000000005
8DDD 2013_FebruaryFalse000000100000000000003
11FFF 2013_OctoberFalse000000100000000000003
12FFF 2013_OctoberFalse000000200000000000003
14GGG 2013_OctoberFalse000000200000000000003
0BBB 2013_FebruaryFalse000000100000000000002
1BBB 2013_FebruaryFalse000000200000000010202
3BBB 2013_OctoberFalse000000200000000000002
4BBB 2013_OctoberFalse000000200000000000012